Using System Identification Toolbox Software with Control System Toolbox Software

This example shows how to create and plot models using the System Identification Toolbox software and Control System Toolbox software.

Construct a random numeric model using the Control System Toolbox software.

rng('default');
sys0 = drss(4,3,2);

rng('default') specifies the setting of the random number generator as its default setting.

sys0 is a fourth-order numeric state-space model with three outputs and two inputs.

Convert sys0 to an identified state-space model and set its output noise variance.

sys = idss(sys0);
sys.NoiseVariance = 0.1*eye(3);

Generate input data for simulating the output.

u = iddata([],idinput([800 2],'rbs'));

Simulate the model output with added noise.

opt = simOptions('AddNoise',true);
y = sim(sys,u,opt);

sim requires System Identification Toolbox software.

opt is an option set specifying simulation options.

y is the simulated output for sys.

Create an input-output (iddata) object.

data = [y u];

Estimate the state-space model from the generated data using ssest.

estimated_ss = ssest(data(1:400));

ssest requires System Identification Toolbox software.

estimated_ss is an identified state-space model.

Convert the identified state-space model to a numeric transfer function

sys_tf = tf(estimated_ss);

tf requires Control System Toolbox software.

Plot the model output for identified state-space model.

compare(data(401:800),estimated_ss)

Plot the response of identified model using the LTI Viewer.

view(estimated_ss);

Using Identified Models for Control Design Applications

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